1. Field of the Invention
The present invention relates in general to an automatic production quality control method and system in the semiconductor manufacturing industry. In particular, the present invention relates to a method and system for overcoming the drawbacks of conventional micro-analytical detection and defect inspection performed by hand, improving the efficiency of quality control in a semiconductor production line.
2. Description of the Related Art
In modern semiconductor manufacturing, various types of defects or failures may occur on the wafers due to unpredictable human factors, mechanical factors, and environmental factors. These defects may cause damage to the integrated circuits formed on the wafers, affecting function and production yield is reduced. As the complexity of the modern semiconductor wafer process grows and the scale of the integrated circuits increases, tiny particles, for example, with a diameter of 0.3 xcexcm, may reduce production yield. In this situation, it is difficult for analysis personnel to analyze various wafer defects, such as identifying which unit processes are responsible for the wafer defects in question, analyzing the defect characteristics of manufacturing stations or machines in the production line, and analyzing the locations of defects or failure on the wafer or dies. In addition, the outcome of these defect analyses heavily depends on the completeness, accessibility, and timeliness of various production data.
FIG. 1 is a flowchart illustrating defect analyses in the conventional semiconductor manufacturing process. The conventional defect analyses of a processed wafer can be divided into two sections, online and offline monitoring, illustrated in the left portion and the right portion of FIG. 1, respectively.
The online monitoring section performs non-destructive and automatic detection in the production line. Generally speaking, diffusion/thin-film unit processes 11, photolithographic unit processes 12 and etching unit processes 13 are necessary in a standard semiconductor process. During these processes, localized defects or failure may occur on the surface and within the wafers due to uncontrollable operational factors. Thus, the inspector in the production line should regularly perform various inspections after developer/etching/thin-film processes 20 using various inline test instruments to examine the failure types of the wafers induced by these unit processes. Next, defect imaging detection 30 is performed on the wafers, for example, by scanning electron microscopes (SEMs), to obtain the defect distribution, defect locations, and the defect images on the wafers.
In the offline monitoring section, the finished wafer is first given a wafer acceptance test (WAT) 40, an electrical test, by appropriate equipment. Next, the wafers are tested by a surface inspection 50 for quality control to test whether the degree of particle-induced defect is within the requirement of the product client. The wafers are sliced into bare dies, each of which is tested by a chip probing (C/P) 60 or wafer probing test to identify good dies on the wafer or obtain production yield. In addition, a reliability analysis 70 is also required to evaluate the reliability characteristics.
Conventionally, various wafer defect data, yield data and inline inspection data in the inline and offline monitoring are collected as production data and stored in a database of a server for further analysis by other personnel.
When wafers in a given lot are prone to defects, thus reducing the total production yield, engineers search the database storing the production data to identify all of the manufacturing machines that have processed the wafers in the same lot. According to the findings of the search, the online engineers first halt the identified manufacturing machines to examine and calibrate the related parameters thereof to lower the possibility of reoccurrence of defect. However, since these calibration steps are manually performed in the conventional semiconductor industry, executive efficiency is quite low and online engineers must repeat the above steps to achieve calibration.
An object of the present invention is to provide a method of automatically controlling production quality of a wafer production line, which can integrate various defect, yield, and online inspection data with a manufacturing executive system (hereafter called MES) to upgrade the efficiency of the operation.
According to the above objective, the present invention provides a method of controlling production quality of a wafer production line. The wafer production line includes a server having a database device, a plurality of manufacturing machines processing corresponding unit processes and a MES coupled to the server controlling the manufacturing machines. This method comprises the steps of:
(a) inspecting wafers of a first lot to generate production data and storing the production data to the database device;
(b) judging whether the wafers of the first lot comply with a predetermined specification by the server according to the stored production data;
(c) identifying the manufacturing machines that have handled non-compliant wafers of the first lot;
(d) notifying the manufacturing executive system of the information of the identified manufacturing machines by the server;
(e) halting the identified manufacturing machines and calibrating parameters thereof by the manufacturing executive system;
(f) processing wafers of a second lot by the identified manufacturing machines;
(g) inspecting the wafers of the second lot;
(h) returning back to step (e) when the wafers of the second lot do not comply with the predetermined specification; and
(i) printing a statistic form when the wafers of the second lot comply with the predetermined specification.